The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Dynamic Time Warping in Gait Classificationof Motion Capture Data


    Beteiligte:

    Erscheinungsdatum :

    2012-11-20


    Anmerkungen:

    oai:zenodo.org:1083929



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




    Randomized time warping for motion recognition

    Suryanto, C. H. / Xue, J. H. / Fukui, K. | British Library Online Contents | 2016


    Speech Recognition using Dynamic Time Warping

    Amin, Talal Bin / Mahmood, Iftekhar | IEEE | 2008


    Word image matching using dynamic time warping

    Rath, T.M. / Manmatha, R. | IEEE | 2003


    Word Image Matching Using Dynamic Time Warping

    Rath, T. / Manmatha, R. / IEEE | British Library Conference Proceedings | 2003


    Spatial De-Interlacing using Dynamic Time Warping

    Almog, A. / Levi, A. / Bruckstein, A. M. | British Library Conference Proceedings | 2005